Method, device, medium and system for structured information generation for orbital images

By performing coarse-to-fine segmentation and feature fusion on the original orbital image, high-precision and fast structured information of the orbital image is generated, which solves the problems of subjective interference in manual interpretation and time-consuming and labor-intensive segmentation models, and improves the accuracy and efficiency of structured information.

CN122417320APending Publication Date: 2026-07-17BEIJING TONGREN HOSPITAL AFFILIATED TO CAPITAL MEDICAL UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
BEIJING TONGREN HOSPITAL AFFILIATED TO CAPITAL MEDICAL UNIV
Filing Date
2026-04-14
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

In existing technologies, the generation of structured information by manually interpreting multi-sequence orbital images is easily affected by subjective factors, resulting in inaccurate information and omission of key features. Furthermore, high-precision segmentation models are time-consuming while fast segmentation models lack sufficient accuracy, making it difficult to balance segmentation accuracy and speed.

Method used

The first segmented image is obtained by coarsely segmenting the original orbital image, and a spatial attention weight map is generated. This map is then used to perform fine segmentation on the original orbital image. The features of the original orbital image, the labeled image, and the segmented image are combined to generate structured information.

Benefits of technology

It achieves high-precision and fast orbital image segmentation, ensuring the accuracy of structured information and the efficiency of generation, and resolving the contradiction between segmentation accuracy and speed.

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Abstract

本申请涉及图像处理技术领域,公开了用于眼眶图像的结构化信息生成方法、设备、介质及系统,该方法包括:获取原始眼眶图像以及与原始眼眶图像对应的标注图像;对原始眼眶图像中的第一感兴趣目标进行分割,得到标注有第一感兴趣目标所处第二区域的第一分割图像;将标注图像与第一分割图像进行比对,得到空间注意力权重图;基于空间注意力权重图,对原始眼眶图像中的第二感兴趣目标进行分割,得到标注有第二感兴趣目标所处第三区域的第二分割图像;利用原始眼眶图像、标注图像和第二分割图像的特征融合结果,生成用于描述第二感兴趣目标的结构化信息。通过实施本申请的方法,可以自动且较为精准地生成结构化信息。
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